Aaron J. Stern

Ohana detects selection in multiple populations by modeling ancestral admixture components, identifying loci with extreme genetic differentiation and new candidate regions in admixed populations.

This paper introduces a method to estimate polygenic adaptation using whole-genome genealogies and GWAS data, finding evidence of directional selection on multiple human traits and correlated responses.

This study uses population genetic simulations to show that genetic rescue efficacy for local adaptations depends on mutational load and polygenicity, with complex traits being more affected.

This paper introduces an approximate full-likelihood method to infer selection and allele frequency trajectories from DNA sequence data, showing improved power to detect selection compared to existing methods.

The paper shows that bacterial species with faster growth rates have more SD-led genes, linking translation initiation mechanisms to growth strategies and environmental conditions.